Kurzfassung

The aim of this work is to improve customers’ acceptance of navigation systems as well as to evenly spread traffic in the case of congested roads by the use of individual driver preferences for route planning.
To make driving safer and simpler, driver assistance systems are increasingly used to prevent the driver from excessive workload in different traffic situations. An increase in driver strain occurs, for example, when navigating an unknown area or driving on congested roads. Such workload is reduced by a navigation system which proposes a route to the driver and guides him around congested roads with uniform planning algorithms based on the fastest or shortest route opti-misation. With the use of uniform planning algorithms in the case of a traffic jam, most drivers get the same detour proposed and this detour is soon congested as well. The support offered by an assistance system has to fulfil the expectations of its user. An assistance system that routes its user from one traffic jam to another, for example, will not be easily accepted. Further, the sub-jective benefit of the support has to be obvious to the individual. This cannot be fulfilled in a uniform way.
The motivation for this work is based on the big differences assumed between the implemented technical solutions for the route planning and the route planning of humans rely on their mental maps. For example, if you ask different drivers which route they would select to reach a given destination in a known area, you get a lot of different possible routes. If you ask them for their reasons for taking a specific route, you get a lot of different answers. Further, if there are signifi-cant differences in the preferred routes that different drivers would take, the planning of a nec-essary detour would lead to different routes being calculated for individual drivers. This in turn would result in a better spread of the traffic on the road network.
The expected result of this work is the knowledge about the criteria or features which are used in human route planning including the individual distribution on the network. Moreover this project gives an indication of the transformation of the physical road map into the mental map of the driver. Based on this information and on the gained differences in the individual route planning, an estimate of the self-spread effect on detours can be calculated.